From 84f29ac7797ce6bb6893b5af7e85f3e707fbd060 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Lo=C3=AFc=20Le=20Guyader?= <loic.le.guyader@xfel.eu>
Date: Thu, 14 Nov 2019 20:28:52 +0100
Subject: [PATCH] Ai fastccd
---
FastCCD.py | 2 +-
azimuthal_integrator.py | 9 ++++++---
2 files changed, 7 insertions(+), 4 deletions(-)
diff --git a/FastCCD.py b/FastCCD.py
index 1b8ca48..6d4b2a1 100644
--- a/FastCCD.py
+++ b/FastCCD.py
@@ -496,7 +496,7 @@ class FastCCD:
im_pumped_mean = im_pumped_arranged.mean(axis=0)
im_unpumped_mean = im_unpumped_arranged.mean(axis=0)
- ai = tb.azimuthal_integrator(im_pumped_mean.shape, center, angle_range, dr=dr)
+ ai = tb.azimuthal_integrator(im_pumped_mean.shape, center, angle_range, dr=dr, aspect=1)
norm = ai(~np.isnan(im_pumped_mean))
az_pump = []
diff --git a/azimuthal_integrator.py b/azimuthal_integrator.py
index e064a39..b84df6c 100644
--- a/azimuthal_integrator.py
+++ b/azimuthal_integrator.py
@@ -1,7 +1,7 @@
import numpy as np
class azimuthal_integrator(object):
- def __init__(self, imageshape, center, polar_range, dr=2):
+ def __init__(self, imageshape, center, polar_range, dr=2, aspect=204/236):
'''
Create a reusable integrator for repeated azimuthal integration of similar
images. Calculates array indices for a given parameter set that allows
@@ -21,6 +21,9 @@ class azimuthal_integrator(object):
dr : int, default 2
radial width of the integration slices. Takes non-square DSSC pixels into account.
+ aspect: float, default 204/236 for DSSC
+ aspect ratio of the pixel pitch
+
Returns
=======
ai : azimuthal_integrator instance
@@ -39,7 +42,7 @@ class azimuthal_integrator(object):
ycoord -= cy
# distance from center, hexagonal pixel shape taken into account
- dist_array = np.hypot(xcoord * 204 / 236, ycoord)
+ dist_array = np.hypot(xcoord * aspect, ycoord)
# array of polar angles
if np.abs(polar_range[1]-polar_range[0]) > 180:
@@ -53,7 +56,7 @@ class azimuthal_integrator(object):
polar_array = np.mod(polar_array, np.pi)
self.polar_mask = (polar_array > tmin) * (polar_array < tmax)
- self.maxdist = min(sx - cx, sy - cy)
+ self.maxdist = max(sx - cx, sy - cy)
ix, iy = np.indices(dimensions=(sx, sy))
self.index_array = np.ravel_multi_index((ix, iy), (sx, sy))
--
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